Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume

Detalhes bibliográficos
Autor(a) principal: Santarosa,Lucas Vituri
Data de Publicação: 2018
Outros Autores: Manzione,Rodrigo Lilla
Tipo de documento: Artigo
Idioma: eng
Título da fonte: RBRH (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100222
Resumo: ABSTRACT Spatial data became increasingly utilized in many scientific fields due to the accessibility of monitoring data from different sources. In the case of hydrological mapping, measurements of external environmental conditions, such as soil, climate, vegetation, are often available in addition to the measurements of water characteristics. An integrated modelling approach capable to incorporate multiple input data sets that may have heterogeneous geometries and other error characteristics can be achieved using geostatistical techniques. In this study, different physical hydric properties of soils extensively sampled and topography were used as auxiliary information for making optimal, point-level inferences of water table depths in forest areas. We used data from 48 wells in the Bauru Aquifer System in the Santa Bárbara Ecological Station (EEcSB), in the municipality of Aguas de Santa Bárbara in São Paulo State, Brazil. Using the resistance of soil to penetration and topography as auxiliary variables helped reduce prediction errors. With the generated maps, it was possible to estimate the volumes of water recovered from the water table in two periods during the monitoring period. These values showed that 30% of the recovered volume would be sufficient for a three-month supply of water for a population of 30,000 inhabitants. Therefore, this raises the possibility of using areas such as the EEcSB as strategic supplies in artificial recharging management.
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spelling Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volumeData fusionGroundwater managementGeostatisticsBauru Aquifer SystemGroundwater rechargeABSTRACT Spatial data became increasingly utilized in many scientific fields due to the accessibility of monitoring data from different sources. In the case of hydrological mapping, measurements of external environmental conditions, such as soil, climate, vegetation, are often available in addition to the measurements of water characteristics. An integrated modelling approach capable to incorporate multiple input data sets that may have heterogeneous geometries and other error characteristics can be achieved using geostatistical techniques. In this study, different physical hydric properties of soils extensively sampled and topography were used as auxiliary information for making optimal, point-level inferences of water table depths in forest areas. We used data from 48 wells in the Bauru Aquifer System in the Santa Bárbara Ecological Station (EEcSB), in the municipality of Aguas de Santa Bárbara in São Paulo State, Brazil. Using the resistance of soil to penetration and topography as auxiliary variables helped reduce prediction errors. With the generated maps, it was possible to estimate the volumes of water recovered from the water table in two periods during the monitoring period. These values showed that 30% of the recovered volume would be sufficient for a three-month supply of water for a population of 30,000 inhabitants. Therefore, this raises the possibility of using areas such as the EEcSB as strategic supplies in artificial recharging management.Associação Brasileira de Recursos Hídricos2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100222RBRH v.23 2018reponame:RBRH (Online)instname:Associação Brasileira de Recursos Hídricos (ABRH)instacron:ABRH10.1590/2318-0331.231820170115info:eu-repo/semantics/openAccessSantarosa,Lucas VituriManzione,Rodrigo Lillaeng2018-06-15T00:00:00Zoai:scielo:S2318-03312018000100222Revistahttps://www.scielo.br/j/rbrh/https://old.scielo.br/oai/scielo-oai.php||rbrh@abrh.org.br2318-03311414-381Xopendoar:2018-06-15T00:00RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)false
dc.title.none.fl_str_mv Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
title Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
spellingShingle Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
Santarosa,Lucas Vituri
Data fusion
Groundwater management
Geostatistics
Bauru Aquifer System
Groundwater recharge
title_short Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
title_full Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
title_fullStr Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
title_full_unstemmed Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
title_sort Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume
author Santarosa,Lucas Vituri
author_facet Santarosa,Lucas Vituri
Manzione,Rodrigo Lilla
author_role author
author2 Manzione,Rodrigo Lilla
author2_role author
dc.contributor.author.fl_str_mv Santarosa,Lucas Vituri
Manzione,Rodrigo Lilla
dc.subject.por.fl_str_mv Data fusion
Groundwater management
Geostatistics
Bauru Aquifer System
Groundwater recharge
topic Data fusion
Groundwater management
Geostatistics
Bauru Aquifer System
Groundwater recharge
description ABSTRACT Spatial data became increasingly utilized in many scientific fields due to the accessibility of monitoring data from different sources. In the case of hydrological mapping, measurements of external environmental conditions, such as soil, climate, vegetation, are often available in addition to the measurements of water characteristics. An integrated modelling approach capable to incorporate multiple input data sets that may have heterogeneous geometries and other error characteristics can be achieved using geostatistical techniques. In this study, different physical hydric properties of soils extensively sampled and topography were used as auxiliary information for making optimal, point-level inferences of water table depths in forest areas. We used data from 48 wells in the Bauru Aquifer System in the Santa Bárbara Ecological Station (EEcSB), in the municipality of Aguas de Santa Bárbara in São Paulo State, Brazil. Using the resistance of soil to penetration and topography as auxiliary variables helped reduce prediction errors. With the generated maps, it was possible to estimate the volumes of water recovered from the water table in two periods during the monitoring period. These values showed that 30% of the recovered volume would be sufficient for a three-month supply of water for a population of 30,000 inhabitants. Therefore, this raises the possibility of using areas such as the EEcSB as strategic supplies in artificial recharging management.
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100222
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100222
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2318-0331.231820170115
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Recursos Hídricos
publisher.none.fl_str_mv Associação Brasileira de Recursos Hídricos
dc.source.none.fl_str_mv RBRH v.23 2018
reponame:RBRH (Online)
instname:Associação Brasileira de Recursos Hídricos (ABRH)
instacron:ABRH
instname_str Associação Brasileira de Recursos Hídricos (ABRH)
instacron_str ABRH
institution ABRH
reponame_str RBRH (Online)
collection RBRH (Online)
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repository.mail.fl_str_mv ||rbrh@abrh.org.br
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